Achieving Brazil's Deforestation Target Will Reduce Fire and Deliver Air Quality and Public Health Benefits.
Achieving Brazil's Deforestation Target Will Reduce Fire and Deliver Air Quality and Public Health Benefits.
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DOI：
10.1029/2022ef003048
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发表时间：
2022-12
期刊：
影响因子：
8.2
通讯作者：
Spracklen, Dominick, V
中科院分区：
文献类型：
--
作者：
Butt, Edward W.;Conibear, Luke;Smith, Callum;Baker, Jessica C. A.;Rigby, Richard;Knote, Christoph;Spracklen, Dominick, V
在亚马逊地区，气候、森林砍伐和森林火灾紧密相关，但包含这些相互作用的火灾模型却很缺乏。我们利用温度、降雨、森林砍伐、土地利用和火灾数据对机器学习模型进行训练，结果表明亚马逊地区火灾的时空模式受到森林砍伐的强烈影响。我们发现，巴西亚马逊地区的森林砍伐率每增加一个百分点，火灾次数就会增加0.44个百分点。我们利用该模型预测，2013年至2020年巴西亚马逊地区森林砍伐率的上升导致2020年火灾次数增加了42%。我们还预测，如果巴西实现了《国家气候变化政策》下的森林砍伐目标，2020年巴西亚马逊地区的火灾次数将会减少32%。利用区域化学 - 气候模型和暴露 - 反应关联，我们估计在这种情况下，由于烟雾排放减少而改善的空气质量将使因细颗粒物暴露减少而导致的死亡人数减少2300人。我们的分析表明，减少巴西亚马逊地区的森林砍伐将带来空气质量和公共健康方面的益处。
利用机器学习方法，我们表明亚马逊地区火灾次数的时空模式受到森林砍伐的强烈影响。
我们表明2013年至2020年巴西亚马逊地区森林砍伐的增加是2020年火灾次数增加42%的原因。
我们估计如果巴西实现了其亚马逊森林砍伐目标，2020年火灾次数将减少32%，空气质量和健康状况也会改善。
Climate, deforestation, and forest fires are closely coupled in the Amazon, but models of fire that include these interactions are lacking. We trained machine learning models on temperature, rainfall, deforestation, land‐use, and fire data to show that spatial and temporal patterns of fire in the Amazon are strongly modified by deforestation. We find that fire count across the Brazilian Amazon increases by 0.44 percentage points for each percentage point increase in deforestation rate. We used the model to predict that the increased deforestation rate in the Brazilian Amazon from 2013 to 2020 caused a 42% increase in fire counts in 2020. We predict that if Brazil had achieved the deforestation target under the National Policy on Climate Change, there would have been 32% fewer fire counts across the Brazilian Amazon in 2020. Using a regional chemistry‐climate model and exposure‐response associations, we estimate that the improved air quality due to reduced smoke emission under this scenario would have resulted in 2,300 fewer deaths due to reduced exposure to fine particulate matter. Our analysis demonstrates the air quality and public health benefits that would accrue from reducing deforestation in the Brazilian Amazon. Using a machine learning approach, we show the spatiotemporal pattern of fire counts in the Amazon is strongly modified by deforestation We show increases in deforestation in the Brazilian Amazon between 2013 and 2020 were responsible for a 42% increase in fire counts in 2020 We estimate 32% fewer fire counts and improved air quality health outcomes in 2020 if Brazil had achieved their Amazon deforestation target